Bibliographic record
Abstract
07–154Bello, Richard (Sam Houston State U, USA; bello@shsu.edu ), Causes and paralinguistic correlates of interpersonal equivocation. Journal of Pragmatics (Elsevier) 38.9 (2006), 1430–1441. 07–155Bosco, Francesca M. (Università e Politecnico di Torino, Italy; bosco@psych.unito.it ), Monica Bucciarelli & Bruno G. Bara, Recognition and repair of communicative failures: A developmental perspective. Journal of Pragmatics (Elsevier) 38.9 (2006), 1398–1429. 07–156Braber, Natalie (U Manchester, UK; natalie.braber@ntu.ac.uk ), Emotional and emotive language: Modal particles and tags in unified Berlin. Journal of Pragmatics (Elsevier) 38.9 (2006), 1487–1503. 07–157Curl, Traci S. (U York, UK; tsc3@york.ac.uk ), Offers of assistance: Constraints on syntactic design. Journal of Pragmatics (Elsevier) 38.8 (2006), 1257–1280. 07–158Hussey, Karen A. (U Western Ontario, Canada) & Albert N. Katz, Metaphor production in online conversation: Gender and friendship status. Discourse Processes (Erlbaum) 42.1 (2006), 75–98. 07–159Ishida, Kazutoh (U Hawaii at Manoa, USA; kazutoh@1994.jukuin.keio.ac.jp ), How can you be so certain? The use of hearsay evidentials by English-speaking learners of Japanese. Journal of Pragmatics (Elsevier) 38.8 (2006), 1281–1304. 07–160Lipovsky, Caroline (U Sydney, Australia; Caroline.Lipovsky@arts.usyd.edu.au ), Candidates' negotiation of their expertise in job interviews. Journal of Pragmatics (Elsevier) 38.8 (2006), 1147–1174. 07–161Mori, J. (U Wisconsin-Madison, USA; jmori@wisc.edu ), The workings of the Japanese token hee in informing sequences: An analysis of sequential context, turn shape, and prosody. Journal of Pragmatics (Elsevier) 38.8 (2006), 1175–1205. 07–162Schegloff, Emanuel A. (U California, Los Angeles, USA; schegloff@soc.ucla.edu ) & Gonen Hacohen, On the preference for minimization in referring to persons: Evidence from Hebrew conversation. Journal of Pragmatics (Elsevier) 38.8 (2006), 1305–1312. 07–163Wang, Jinjun (Yunnan U, China), Questions and the exercise of power. Discourse & Society (Sage) 17.4 (2006), 529–548. 07–164Wouk, Fay (U Auckland, New Zealand; f.wouk@auckland.ac.nz ), The language of apologizing in Lombok, Indonesia. Journal of Pragmatics (Elsevier) 38.9 (2006), 1457–1486.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.112 | 0.041 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".